Create config.json

config.json

@@ -0,0 +1,59 @@
+{
+  "Model": "CogniFusion-XTTS-slerp",
+  "Description": "CogniFusion-XTTS-slerp is a merge of the following models using LazyMergekit: Or4cl3-1/cognitive-agent-xtts-optimized and Or4cl3-1/multimodal-fusion-optimized",
+  "Configuration": {
+    "slices": [
+      {
+        "sources": [
+          {
+            "model": "Or4cl3-1/cognitive-agent-xtts-optimized",
+            "layer_range": [0, 32]
+          },
+          {
+            "model": "Or4cl3-1/multimodal-fusion-optimized",
+            "layer_range": [0, 32]
+          }
+        ]
+      }
+    ],
+    "merge_method": "slerp",
+    "base_model": "Or4cl3-1/cognitive-agent-xtts-optimized",
+    "parameters": {
+      "t": [
+        {
+          "filter": "self_attn",
+          "value": [0, 0.5, 0.3, 0.7, 1]
+        },
+        {
+          "filter": "mlp",
+          "value": [1, 0.5, 0.7, 0.3, 0]
+        },
+        {
+          "value": 0.5
+        }
+      ]
+    },
+    "dtype": "bfloat16"
+  },
+  "Ethical Considerations": "Add ethical considerations and any additional optimization parameters here",
+  "Usage": {
+    "Installation": "!pip install -qU transformers accelerate",
+    "Code": [
+      "from transformers import AutoTokenizer",
+      "import transformers",
+      "import torch",
+      "model = \"Or4cl3-1/CogniFusion-XTTS-slerp\"",
+      "messages = [{\"role\": \"user\", \"content\": \"What is a large language model?\"}]",
+      "tokenizer = AutoTokenizer.from_pretrained(model)",
+      "prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)",
+      "pipeline = transformers.pipeline(",
+      "    \"text-generation\",",
+      "    model=model,",
+      "    torch_dtype=torch.float16,",
+      "    device_map=\"auto\",",
+      ")",
+      "outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)",
+      "print(outputs[0][\"generated_text\"])"
+    ]
+  }
+}